#hard_start = 0 hard_start = eventpaths.index(boxpath + '/cutdata_s/Event_2010_06_13_03_08_57/AZ_PFO_HHE__2010_06_13_03_08_57.SAC') print(hard_start) #read in cut data, rmean and rtrend, find .resp file, correct and add to icorr dir for i in range(hard_start,len(eventpaths)):#in this case event paths are all sac files base = path.basename(eventpaths[i]) print 'correcting file: ' + base folder = eventpaths[i].split('/')[-2] network = base.split('_')[0] station = base.split('_')[1] full_channel = base.split('_')[2] #find response file respfile = response_path + '/' + network + '.' + station + '.' + channel + '.resp' #first rmean and rtrend stream = read(eventpaths[i]) tr = stream[0] #check and make sure that the trace isn't empty if(tr.stats.npts > 0): tr.detrend(type = 'demean')#removes mean of data tr.detrend(type = 'simple')#rtrend linear from first and last samples #rewrite to a sac file tr.write('temp.sac', format = 'sac') sacfile = 'temp.sac' icorr_sacfile = icorr_path + '/' + folder + '/'+ base #uncorrected_sac_file,resp_file,corrected_sac_file,water_level_bds,resp_unit wf.remove_response(sacfile,respfile,icorr_sacfile,prefilt,tsunit)#prefilt values for HH
raw_file_N = boxpath + '/cutdata_s/Event_' + eventid + '/' + network + '_' + station + '_HHN_' + loc + '_' + eventid + '.SAC' prefilt = (0, 0.4, 35, 50) respfile = top_dir + '/boxes/' + box + '/respfiles/' + network + '.' + station + '.HH*.resp' tsunit = 'VEL' icorr_sacfile = top_dir + '/boxes/' + box + '/icorrN.SAC' stream = read(raw_file_N) tr = stream[0] # tr.detrend(type = 'demean')#removes mean of data # tr.detrend(type = 'simple')#rtrend linear from first and last samples #rewrite to a sac file tr.write('temp.sac', format='sac') sacfile = 'temp.sac' wf.remove_response(sacfile, respfile, icorr_sacfile, prefilt, tsunit) stream = read(icorr_sacfile) tr = stream[0] dataN = tr.data raw_file_E = boxpath + '/cutdata_s/Event_' + eventid + '/' + network + '_' + station + '_HHE_' + loc + '_' + eventid + '.SAC' respfile = top_dir + '/boxes/' + box + '/respfiles/AZ.BZN.HH*.resp' tsunit = 'VEL' icorr_sacfile = top_dir + '/boxes/' + box + '/icorrE.SAC' stream = read(raw_file_E) tr = stream[0] # tr.detrend(type = 'demean')#removes mean of data # tr.detrend(type = 'simple')#rtrend linear from first and last samples #rewrite to a sac file
# st = stream tr = stream[0] ny = tr.stats.sampling_rate * 0.5 print ny # ny = 0.125 #################### prefilt = (0.0, 0.01, 0.7 * ny, ny) tr.detrend(type='demean') #removes mean of data tr.detrend(type='simple') #rtrend linear from first and last samples #rewrite to a sac file tr.write('temp.sac', format='sac') sacfile = 'temp.sac' icorr_sacfile = icorr_path + '/' + base wf.remove_response(sacfile, respfile, icorr_sacfile, prefilt, 'VEL') #, plot=True)#prefilt values for HH f = glob.glob(workingdir + 'corrected/*.sac') for i in range(len(f)): st = read(f[i]) name = (f[i].split('/')[-1])[0:-4] #.split('.')[0:4] print name fig = st.plot() fig.savefig(workingdir + 'corrected/' + name + '.png') #f = glob.glob(workingdir + 'corrected/*.sac') #for i in range(len(f)): # st = read(f[i]) # name = (f[i].split('/')[-1])[0:-4]#.split('.')[0:4] # print name ## st.filter("bandpass", freqmin=.001, freqmax=0.125,corners=2, zerophase=False)